Methods, systems, and devices are disclosed for an efficient hardware architecture to implement gradient boosted trees for detecting biological conditions. For example, a method of detecting a biological condition includes receiving, by a device, a plurality of physiological signals from a plurality of input channels of the device, selecting, based on a trained prediction model, one or more input channels from the plurality of input channels, converting the one or more physiological signals received from the one or more input channels to one or more digital physiological signals, identifying, by using the plurality of gradient boosted decision trees, the selected characteristic in the one or more digital physiological signals, and determining a presence of a physiological condition based on an addition of the output values obtained from the plurality of gradient boosted decision trees.

Neurological abnormalities are often discovered through observation by health care providers, and/or parent report. Many neurodevelopmental disorders such as ASD are purely identified through behavioral analysis, and cannot be screened for using a biomarker or quantitative stimulus-response test. Current screening tools contain subjective components based on parent report and clinician observation, vary in consistency of use across providers, and demands resources, knowledge, and access to skilled expertise. As a result, the only tests used today require lengthy and subjective behavioral analysis and often, miss or misidentify neurodevelopmental disorders contributing to a delayed diagnosis. The technology disclosed herein allow for a solution to this systemic problem.

In an approach for presenting information on an object to be observed, a processor obtains information from a sensor about an object. A processor predicts a time period in which the object is expected to be at a location and in a state, based on historical data, obtained from the sensor, associated with the object. A processor determines whether the object is at the location and in the state within the time period. A processor presents information to a user, wherein the information is about the object.

Methods, systems, and apparatus for detecting and/or validating a detection of a state change by matching the shape of one or more of an cardiac data series, a heart rate variability data series, or at least a portion of a heart beat complex, derived from cardiac data, to an appropriate template.

A wearable system for epileptic seizure detection, comprising an eyeglasses frame, with a left arm and a right arm configured to rest over the ears of an intended person wearing the eyeglasses, a first pair of electrodes located in the left arm, and a second pair of electrodes located in the right arm, the first pair of electrodes and the second pair of electrodes arranged such to be in contact with the skull of the intended person wearing the eyeglasses, and an EEG signal acquiring system integral to the left and right arms, connected to measuring outputs of the respective first pair and second pair of electrodes.

An electrical stimulation controlling device and an electrical stimulation system are provided. In which, the electrical stimulation controlling device includes a receiving circuit and a controller coupled to the receiving circuit. The receiving circuit is configured to receive an ictal neural signal which is a signal obtained by a detector when a neural event has been occurring. The controller is further coupled to a stimulator and configured to: determine a time point to start an electrical stimulation according to the ictal neural signal after an onset of the neural event has been determined; and generate and transmit a control signal to the stimulator for providing the electrical stimulation according to the determined time point.

In some aspects, a sensor includes an optical transmitter that transmits to a brain of a person infrared radiation, and an acoustic receiver that detects an ultrasound signal generated in the brain in response to the infrared radiation. A processor determines oxygen saturation of the brain based on the detected ultrasound signal. The sensor may be included in a cap worn by the person, implanted under the skin of the person, or inserted through the nasal canal of the person.

In some aspects, a closed-loop system for monitoring and/or treating brain function of a person includes a CMUT device that transmits ultrasound radiation to the brain of the person and receives and detects an ultrasound signal generated in the brain, and a processor that assesses the received ultrasound signal to determine brain function and controls further transmission of ultrasound radiation from the CMUT device based on the determined brain function.

A veterinary telemedicine system and method for remote diagnosis of pets. The veterinary telemedicine system and method generally includes a library of pet behaviors associated with an individual pet, each behavior comprising a data signature associated with the behavior. The system includes a local computer, which may be a smartphone, adapted to receive a set of data from a plurality of sensors and further adapted to transmit the set of data to a cloud database. The system also includes a smart collar wearable by a pet and comprising a sensor adapted to track a behavior of the pet and further adapted to communicate with the local computer to provide the local computer with pet behavior data from the sensor. The library of pet behaviors is stored on the cloud database and is usable to diagnose pet health via machine learning/artificial intelligence.

Systems and methods for monitoring patient for syncope are discussed. A syncope monitor system can detect a precipitating event associated with a syncope onset, and acquire hemodynamic data in response to the detection of the precipitating event. A syncope analyzer circuit may generate temporal profiles of one or more hemodynamic parameters using the hemodynamic data. The syncope analyzer may use the temporal profiles to detect a syncopal event and to classify the syncopal event into one of a plurality of syncope categories. The detection and classification information may be output to a user or a process.